Dynamic pricing of electricity in retail markets

This paper aims at defining a dynamic and flexible tariff structure for a distribution company that protects the retail consumers against the excessive fluctuations of the wholesales market prices. We propose a two-stage pricing scheme that sets in a first-stage a time-of-use tariff that is corrected later by a dynamic component once the real-time demand has been observed. A personalized tariff scheme may be offered by a distribution company to each dynamic customer by allowing him to choose the appropriate robustness level expressed in terms of variability between the first and the second-stage decisions. The arising limited recourse model has been tested on realistic test problems, by using a slight modification of a recently proposed interior point solution framework.      

A rewarding-punishing coordination mechanism based on Trust in a divergent supply chain

Coordination of decentralized supply chains using contract design is a problem that has been widely addressed in the literature. We consider a divergent supply chain including a supplier and several retailers producing fashion products with short sale seasons. The retailers cooperate with the supplier as sales agents; i.e., they work in the framework of revenue sharing contracts. Because of their proximity to the market, retailers can provide more accurate demand forecasts to the supplier that is used to decide on issues such as capacity building and market prices with regard to retailers stiff due dates, different lead times and different price-dependent demand functions. To ensure abundant supply and cope with the demand variability, the retailers have an incentive to exaggerate their private forecast information. In this study, we propose a new rewarding-punishing coordination mechanism based on trust between supply chain tiers, considered as a differentiation factor between honest and deceptive partners. An optimization model is developed as a building block of this mechanism. An approximation method is used to simplify and solve the problem. The model is then implemented using Monte-Carlo simulation in four different situations, according to 10 different strategies for forecast information sharing. The findings from the tests show that the mechanism including trust as a decisional factor performs better than ‘No Trust’ mechanism in all situations. These results suggest that taking into account Trust in designing coordination mechanism may have significant influence on the financial performance of the supply chain.     

基于消费者效用模型的贵重首饰经销商决策行为研究

以异质性消费者为对象,研究关税税率调整对贵重首饰经销商决策行为的影响。在个人理性与激励相容的约束条件下,构建基于异质性消费者效用模型的需求函数,分析不同市场类型下经销商的最优决策选择。考虑消费者价格敏感度对社会福利的影响,并在此基础上分析了最优关税税率水平。研究发现:(1)贵重首饰经销商决策行为不仅受政府关税税率的影响,还受消费者价格敏感度的影响;(2)在消费者价格敏感度一定的前提下,若想通过关税来调控贵重首饰市场,关税税率应该控制在一定的区间范围;(3)在关税税率一定的条件下,贵重首饰市场的类型主要受消费者价格敏感度的影响。     

Optimizing product service system by franchise fee contracts under information asymmetry

This paper studies the problem of how to effectively provide product service system (PSS) in a service-oriented manufacturing supply chain under asymmetric private demand information. The PSS in the supply chain is operated heterogeneously and complementarily, in which the manufacturer provides the product while the retailer who possesses private demand information is responsible for adding the necessary value-added service on the basic product. We address the issue of how different contracts affect the decisions and profitability of the supply chain members. Three types of contracts are developed to help supply chain partners to make decisions and enhance the supply chain’s efficiency. The first is the franchise fee (FF) contract, under which the manufacturer provides a two-part tariff contract (wholesale price and franchise fee) to influence the retailer’s decision and to detect her private demand information. The second is the franchise fee with service requirement (FFS) contract, under which the manufacturer specifies the service level required in addition to the two-part tariff contract terms. The third is the franchise fee with centralized service requirement (FFCS) contract, which is similar to the FFS contract but that the service level specified by the manufacturer is the system optimal solution. Our analytical results show that all three contracts enable the manufacturer to detect the retailer’s private demand information, with the FFCS contract achieving the greatest channel profit. Finally, numerical examples are presented, and sensitivity analysis of service level and profit are conducted to compare the performance of the three contracts under different settings. The paper provides managerial guidelines for the manufacturer in contract offering under different conditions.     

碳税政策下时变需求依赖库存与价格的供应链协调模型

研究由一个供应商和一个零售组成的二级供应链系统在碳税政策下的协调问题.对于市场需求率为时变函数且依赖于当前库存水平和销售价格的情形,建立分散式和集中式供应链决策模型.比较两种模型得出供应商和零售商合作能够提高供应链的整体利润但是也会产生更多的碳排放.分别利用批发价格契约和两部收费契约协调分散式决策模型得出供应链协调的条件.最后通过数值算例验证理论结果并分析碳税单价对供应链在两部收费契约下实现协调的影响.     

The valuation of options on capacity with cost and demand uncertainty

Options contracts can provide trading partners with enhanced flexibility to respond to uncertain market conditions and allow for superior capacity planning thanks to early information on future demand. We develop an analytical framework to value options on capacity for production of non-storable goods or dated services. The market consists of a sequence of contract and spot market. Reservations are made during the contract market session in period 0, where the buyer’s future demand, the seller’s future marginal costs as well as the future spot price are uncertain, the latter being impacted neither by the buyer nor the seller. During the spot market session in period 1, the buyer may execute his options or satisfy his entire or additional demand from a competing seller in the spot market. The seller allocates reserved capacity now being called and attempts to sell remaining capacity into the spot market. Analytical expressions for the buyer’s optimal reservation quantity and the seller’s tariff are derived, making explicit the risk-sharing benefits of options contracts. The combination of an options contract and a spot market is demonstrated to be Pareto improving as compared to alternative market schemes. An analysis of the determinants of the efficiency gain characterizes industries particularly suitable to the options approach.     

Strategic tariff equilibrium and optimal tariffs

For constant production and demand given by the linear expenditure system we prove for m goods, n countries a unique optimum tariff and strategic tariff equilibrium exists. We also compute various other quantities and give algorithms for computation of optimum tariffs     

Design of contract parameters in a closed-loop supply chain

We study an extended joint economic lot size problem which incorporates the return flow of remanufacturable used products. The supply chain under consideration consists of a single supplier and a single buyer. The buyer orders a single product from the supplier, uses it for her own needs, and collects the remanufacturable items after use. The ordered items are shipped from the supplier to the buyer in the lot-for-lot fashion by a vehicle which also returns the collected used items from the buyer to the supplier for remanufacturing and subsequent service of the buyer’s demand in the next order cycle. For satisfying the total demand, the supplier manufactures new items or remanufactures used ones received from the buyer. For given demand, productivity, collection rate, disposal cost, setup cost, order cost, holding cost for serviceable and nonserviceable products at the supplier as well as the buyer the lot size (order size) for the supplier (buyer) has to be found which minimizes the total cost. Furthermore, we address a decentralised decision making of the parties under a two-part tariff and determine their equilibrium strategies within the Nash framework.     

突发事件下两部收费契约协调闭环供应链研究

本文针对由一个制造商和一个零售商组成的零售商负责回收闭环供应链的协调问题,首先设计了稳定环境下两部收费契约协调闭环供应链模型。在此基础上,针对突发事件影响下造成零售商面临的市场需求发生变化时,运用K-T条件对集中式决策下的闭环供应链的最优利润进行求解,给出了最优应对策略。通过研究表明:当突发事件发生时,原适用于稳定环境下的两部收费契约将不再对分散式决策下的闭环供应链起协调作用。为此,本研究给出了两种协调策略,一是在制造商自身承担突发事件引起的偏差成本的情况下,通过对原有的两部收费契约中的批发价格和回收价格进行改进;二是若由零售商承担偏差成本,则可保持原有的两部收费契约中的批发价格和回收价格不变。在两种策略下,制造商和零售商均通过重新讨价还价确定合适的固定费用,可协调突发事件影响下的闭环供应链,并证明了两种协调策略的可行性。     

A generic approach to measuring the machine flexibility of manufacturing systems

Despite extensive studies on the flexibility of manufacturing systems over the last two decades, a unified measurement approach has not been developed. To this end, we integrate two domains of machine flexibility models from the literature: operational capability-based machine flexibility and time and cost-based machine flexibility, and propose a generic model to measure machine flexibility with consideration of uncertainties in the system. Furthermore, in our approach we include part characteristics such as processing time and processing cost, the number of operations that a machine can perform, and uncertainties in demand and machine-part assignment. The resulting framework to measure machine flexibility is a two-stage model: a super efficiency Data Envelopment Analysis Model and a flexibility model. The results show that the marginal system machine flexibility does not always increase as the number of operations that a machine can perform increases, and the system machine flexibility depends on the demand uncertainty.     

Coordination mechanisms of supply chain systems

Supply chain management (SCM) has become an important management paradigm. As supply chain members are often separate and independent economic entities, a key issue in SCM is to develop mechanisms that can align their objectives and coordinate their activities so as to optimize system performance. In this paper, we provide a review of coordination mechanisms of supply chain systems in a framework that is based on supply chain decision structure and nature of demand. This framework highlights the behavioral aspects and information need in the coordination of a supply chain. The identification of these issues points out several directions of future research in this area.     

A framework for solving network revenue management problems with customer choice behavior

Revenue management is the process of understanding, anticipating and influencing consumer behavior in order to maximize revenue. Network revenue management models attempt to maximize revenue when customers buy bundles of multiple resources. The dependence among the resources in such cases is created by customer demand. Network revenue management can be formulated as a stochastic dynamic programming problem whose exact solution is computationally intractable. Solutions are based on approximations of various types. Customer choice behavior modeling has been gaining increasing attention in the revenue management. A framework for solving network revenue management problems with customer choice behavior is proposed. The modeling and solving framework is composed from three inter-related network structures: basic network model, Petri net, and neural net.     

Supply chain network capacity competition with outsourcing: a variational equilibrium framework

This paper develops a supply chain network game theory framework with multiple manufacturers/producers, with multiple manufacturing plants, who own distribution centers and distribute their products, which are distinguished by brands, to demand markets, while maximizing profits and competing noncooperatively. The manufacturers also may avail themselves of external distribution centers for storing their products and freight service provision. The manufacturers have capacities associated with their supply chain network links and the external distribution centers also have capacitated storage and distribution capacities for their links, which are shared among the manufacturers and competed for. We utilize a special case of the Generalized Nash Equilibrium problem, known as a variational equilibrium, in order to formulate and solve the problem. A case study on apple farmers in Massachusetts is provided with various scenarios, including a supply chain disruption, to illustrate the modeling and methodological framework as well as the potential benefits of outsourcing in this sector.     

A fuzzy opportunity and threat aggregation approach in multicriteria decision analysis

Economic expansion in developed countries coupled with dramatically growing economies in countries such as China and India have precipitated a steady increase in demand for oil and natural gas. The Caspian Sea region holds large quantities of both oil and natural gas. Because the Caspian Sea is landlocked and the region’s nations are distant from the largest energy markets, transportation must at least begin by pipeline. While some lines currently exist, pipelines with the capacity of transporting larger amounts of energy resources must be constructed to meet the global demand. This study is conducted for a multinational oil and natural gas producer to develop a multicriteria decision analysis (MCDA) framework for evaluating five possible pipeline routes in the Caspian Sea region. The proposed MCDA model considers a large number of conflicting criteria in the evaluation process and captures decision makers’ (DMs’) beliefs through a series of intuitive and analytical methods such as the analytic network process and fuzzy scoring. A defuzzification method is used to obtain crisp values from the subjective judgments and estimates provided by multiple DMs. These crisp values are aggregated and synthesized with the concept of entropy and the theory of the displaced ideal. The alternative routes are plotted on a diagram in a polar coordinate system and a classification scheme is used along with the Euclidean distance to measure which alternative is closer to the ideal route.     

Innovation as a policy strategy for natural resource protection

Growing global food demands place major strains on water resources, including quality impairments and increased water scarcity. Drawing on the largely separate bodies of literature on externalities and technological innovation, this article develops a dynamic framework to explore the long‐term impacts of alternative policy approaches to the agricultural impacts on water resources. Environmental policies, which focus on correcting environmental externalities, lead to an overall gain because costs to farmers are more than offset by reduced environmental damages. Technology policies, which direct public investments into agricultural eco‐innovations, lead to benefits for farmers as well as the environment. Joint implementation of both types of policies leads to the largest overall gain. In principle, a technology policy alone could have greater environmental benefits than an environmental policy alone. This outcome is most likely in cases where the productivity effect of new technology is large and the cost of research is low. Recommendations for research managers

• As an alternative to traditional environmental policy, investments in research can provide win–win solutions that benefit the environment and agricultural producers.
• Conceivably, eco‐innovations could lead to environmental conditions that are better than those achieved by environmental policy alone.
• Adding research investments to existing environmental policy would lead to further improvements in environmental quality while also benefitting farmers.
• Unlike environmental policies that are perceived to impose costs on agriculture, technology policies impart benefits to farmers and are less likely to face political opposition from industry.
• Technology policies are likely to be the most effective when eco‐innovation leads to technologies that meaningfully reduce environmental impacts and also raise farm productivity.

     

Coordinating lead times and safety stocks under autocorrelated demand

We consider a supply chain in which orders and lead times are linked endogenously, as opposed to assuming lead times are exogenous. This assumption is relevant when a retailer’s orders are produced by a supplier with finite capacity and replenished when the order is completed. The retailer faces demands that are correlated over time – either positively or negatively – which may, for example, be induced by a pricing or promotion policy. The auto-correlation in demand affects the order stream placed by the retailer onto the supplier, and this in turn influences the resulting lead times seen by the retailer. Since these lead times also determine the retailer’s orders and its safety stocks (which the retailer must set to cover lead time demand), there is a mutual dependency between orders and lead times. The inclusion of endogenous lead times and autocorrelated demand represents a better fit with real-life situations. However, it poses some additional methodological issues, compared to assuming exogenous lead times or stationary demand processes that are independent over time. By means of a Markov chain analysis and matrix analytic methods, we develop a procedure to determine the distribution of lead times and inventories, that takes into account the correlation between orders and lead times. Our analysis shows that negative autocorrelation in demand, although more erratic, improves both lead time and inventory performance relative to IID demand. Positive correlation makes matters worse than IID demand. Due to the endogeneity of lead times, these effects are much more pronounced and substantial error may be incurred if this endogeneity is ignored.     

The Potential for Endogeneity Bias in Data Envelopment Analysis

Data envelopment analysis has become an important technique for modelling the relationship between inputs and outputs in the production process, particularly in the public sector. However, whenever measures of the output of public sector activity receive public attention, there is a strong possibility that there will be a feedback from the achieved output to the resources devoted to the activity. In other words, the level of resources is endogenous. The implications of such endogeneity for standard econometric estimation techniques are well known, and methods exist to deal with the problem. Most commentators have assumed that endogeneity poses no analogous problems for DEA because the technique merely places an envelope around feasible production possibilities. Using Monte Carlo simulation techniques, however, this paper shows that the efficiency estimates generated by DEA in the presence of endogeneity can be subject to bias, in the sense that inefficient units using low levels of the endogenous resource may be set tougher efficiency targets than equally inefficient units using more of the resource, particularly when sample sizes are small. The paper concludes that, in such circumstances, great caution should be exercised when comparing efficiency measures for units using different levels of the endogenous input.     

产业结构与水资源相关分析理论及其实证

由于不同的产业部门和生活方式对水资源的消耗是不同的，经济的不同发展格局会在很大程度上改变水的需求，因此对宏观经济系统和水资源系统同时进行动态分析，才能揭示它们之间的内在联系。本以北京市为实例，利用相关分析理论和方法，系统地研究了产业结构调整与水资源需求变化之间的关系，同时通过计算，指出北京市产业结构与用水量之间存在着高度相关关系，发展第三产业，调整第二产业是解决首都水资源紧缺的重要方法。     

Joint demand and capacity management in a restaurant system

This paper studies the demand and capacity management problem in a restaurant system. A queueing-based optimization model with underlying quasi birth-and-death process and state-dependent functions is developed to address the dynamic and nonlinearity difficulties. In particular, our model explicitly captures the demand changes with respect to the system congestion state on a near real-time dynamic basis. With this framework, we empirically examine the relative performance of commonly used strategies for the case of a local restaurant. The study shows that a strategy that balances service quality and cost yields maximum profit. The result indicates that the traditional view of the conflict between service quality and cost can be overcome by using an interdisciplinary perspective of marketing and operations. Both perspectives should be embraced in academic research and industrial practice in capacity planning decisions for services.     

Residential water demand model under block rate pricing: A case study of Beijing,China

In many cities, the inconsistency between water supply and water demand has become a critical problem because of deteriorating water shortage and increasing water demand. Uniform price of residential water cannot promote the efficient water allocation. In China, block water price will be put into practice in the future, but the outcome of such regulation measure is unpredictable without theory support. In this paper, the residential water is classified by the volume of water usage based on economic rules and block water is considered as different kinds of goods. A model based on extended linear expenditure system (ELES) is constructed to simulate the relationship between block water price and water demand, which provide theoretical support for the decision-makers. Finally, the proposed model is used to simulate residential water demand under block rate pricing in Beijing.